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All Journal Jurnal Manajemen dan Agribisnis Ahkam: Jurnal Ilmu Syariah Cakrawala Pendidikan Foristek English Language and Literature AL-Daulah Jurnal Online Mahasiswa (JOM) Bidang Ilmu Hukum Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Journal of Aquatropica Asia Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi Panrita Abdi - Jurnal Pengabdian pada Masyarakat Panggung Jurnal Ilmiah Universitas Batanghari Jambi SPEKTRA: Jurnal Kajian Pendidikan Sains Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Hukum tora: Hukum mengatur dan melindungi masyarakat Prosiding Seminar Nasional Pakar Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat Jurnal Mina Sains Jurnal Keperawatan Suaka Insan Jurnal Keperawatan Respati Yogyakarta Al-Munawwarah : Jurnal Pendidikan Islam ALSINATUNA International Journal of Informatics and Computation Jurnal Teknodik As-Syar'i : Jurnal Bimbingan & Konseling Keluarga AVERROUS: Jurnal Kedokteran dan Kesehatan Malikussaleh Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Idea Hukum Proceeding International Seminar of Islamic Studies Hunafa: Jurnal Studia Islamika Jurnal Neuroanestesi Indonesia Jurnal Aplikasi IPTEK Indonesia Collaborate Daily Book Series
Hamzah Hamzah
State University of Makassar
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Journal : International Journal of Informatics and Computation

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Efficient Fruits Classification Using Convolutional Neural Network ADNAN ADNAN ABIDIN; Hamzah Hamzah; Marselina Endah
International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i1.31

Abstract

Classification of fruits is a growing research topic in image processing. Various papers propose various techniques to deal with the classification of apples. However, some traditional classification methods remain drawbacks to producing an effective result with the big dataset. Inspired by deep learning in computer vision, we propose a novel learning method to construct a classification model, which can classify types of apples quickly and accurately. To conduct our experiment, we collect datasets, do preprocessing, train our model, tune parameter settings to get the highest accuracy results, then test the model using new data. Based on the experimental results, the classification model of green apples and red apples can obtain good accuracy with little loss. Therefore, the proposed model can be a promising solution to deal with apple classification.
Co-Authors A. Sitti Chairunnisa Abd Haris Djalante ade muhamad putra ADNAN ADNAN ABIDIN Ahmad Faizal Akhmad Syahri Alfa Astiana Afandi Amiluddin Amiluddin Andi Dian Eka Anggriani Ardi Amir Arie Utariani Asti Proborini Atika Yunia Rahayu Awaluddin Awaluddin Bambang Hariyadi Benny Audi Jaya Gosari Budi Suhartono Candra Wijaya Chair Rani Dasrol Dasrol David Setiawan Deni Ariyati Desi Sukenti Didik Aribowo Djafar, Wihdat Eflita Meiyetriani Elizeus Hanindito Erma Linda Siregar Farid Samawi Firman Firman Florensia, Lima Gusti Melia Hasani, Chasyim Helda Iriani Hutwan Syarifuddin Imam Teguh Saptono Imam Tholkhah Imran Ariadin Ira Kurniawati Latifa Siswati Leilea Azizathul Mukhtiya Lensi Erika Novianti M Zaim M. Rizal Firmansyah M. Yusuf Ahmad Mansyur Hasbullah Marimin . Marselina Endah Hiswati Marwoto Marwoto Maryantho Masarrang Maryono Maryono Mashitah Sabdin Mimi Mimi Amaludin Misliah Indrus Muflih Muflih Muhamad Faqihudin Muhsinin Muhsinin Murjani Murjani Murjani Nanang Nurofik Paulus Mudjihartono Prabowo Tjitropranoto Prananda Surya Airlangga Ratu Bai Rohimah Rica Rian Rifkah Fitriah Semedi, Bambang Pujo Seprita Lidar Sintiya Stephani Sitti Fakhriyyah Sri Jumini Suarni Suarni Sumardjo Sumardjo Suryanti Suryanti Suyoto Suyoto Syahraini Tambak Usaha Situmeang Wahyuddin Wahyuddin Yandri Yandri Yoga Yuniadi Yuliani Budiyarti Yulius S. Pirade Zannatunnisya Zannatunnisya Zulfikar Jayakusuma